Updates

Model and report changes

  1. We have extended the use of serological sampling data to use samples taken beyond the first wave of the pandemic. The samples are those collected by NHS Blood and Transplant using the Roche-N assay, which measures the prevalence of infection-acquired antibodies in the population.
  2. The model now accounts for the ongoing immunisation programme, stratifying the population of people still susceptible to infection with the virus according to their immunisation status (unimmunised/1 dose/2 doses). We use data on the daily proportions of the population getting immunised to inform this splitting of the population, assuming that it takes three weeks for vaccine-derived immunity to develop. Vaccine efficacy is assumed against both infection and death, using values for the efficacy in agreement with those found here. We have a changepoint in the vaccine efficacy on the 10th May, which marks a transition from alpha being the dominant variant, to delta.
  3. The model also accounts for a different susceptibility to infection in each adult age group (no prior information is used); and for the under-15s, (using prior information from Viner et al, 2020, which estimates children to be less likely to acquire infection when in contact with an infectious individual).
  4. The model has the ability to incorporate estimates of community prevalence, by region and age group, from the Office of National Statistics COVID-19 Infection Survey (see Data Sources for details). These are included weekly since the outset of the Survey in May 2020 for the age groups >4 years to inform trends in incidence that are too recent to be captured by the data on deaths.
  5. The underlying probability of an unvaccinated individual dying following infection with SARS-CoV2 (the infection-fatality rate, IFR) is allowed to change gradually over the course of 30 days every (approximately) 100 days. This is designed to reflect fluctuations due to seasonal effects, demand on healthcare services or the emergence of new virus variants of differing severity.
  6. The ‘Epidemic summary’ only reports the current value for the IFR by age. To visualise how this has changed over time in our model, see the IFR tab in the ‘Infections and Deaths’ section of the report. The quantity that is now plotted under this tab is the probability of dying if infected, taking into account the impact of the immunisation programme - it is an average of a lower rate of death in vaccinated individuals and a higher rate among the unvaccinated.

Updated findings

  1. The estimate of the daily number of new infections on the 29th October across England is 74,600 (65,900–85,000, 95% credible interval). The daily infection rate is estimated to be 133 per 100k population per day nationally. The highest rates are still in the South West (SW) and now in the South East (SE) with 219 and 181 infections per 100K population, corresponding to 12,200 and 16,500 daily infections respectively. These are followed by the East Midland (EM), East of England (EE) and London (GL) with 133, 132 and 128 infections per 100k respectively. The North East (NE), West Midlands (WM) and Yorkshire and the Humber (YH) have daily infection rates around 100 per 100k, while the North West (NW) has the lowest at 72 infections per 100k. Note that a substantial proportion of these infections will be asymptomatic.
  2. The daily number of deaths continues to increase, such that we forecast between 144 and 229 deaths per day by the 19th of November, following a peak on the 16th.
  3. This week it is unlikely that Rt is bigger than 1 in any region, though this is likely only due to the presence of the half-term school holiday. Immediately prior to the school holiday, Rt was greater than 1 in three regions: GL, SE, SW.
  4. The growth rate for England remains at -0.03 (-0.03– -0.02) per day. This means that, nationally, the number of infections is decreasing, corresponding to an Rt of around 0.8.
  5. Our estimates for the attack rate, that is the proportion of the regional populations who have ever been infected, are consistent with last week, with GL at 59% and NE at 58%. WM, NW and YH are all also above the national average with 54%, 51% and 50% respectively.The SE and SW continue to have the lowest attack rates at 37% and 36%.
  6. Note that the deaths data used are only very weakly informative on Rt over the last two weeks. Therefore, the estimate for current incidence, Rt and the forecast of daily numbers of deaths are likely to be subject to some revision.

Interpretation

Our estimates show a pandemic with an Rt that is firmly, but perhaps only transiently, below 1, as a result of the half-term school holiday, following a sustained period of increasing infections that had been converging to a plateau. The pandemic data that we use typically inform incidence up until about two weeks ago. At this time, in five out of nine regions the probability that Rt is greater than 1 is in excess of 50%. The increase in the number of deaths tentatively identified last week has continued this week. Our model predicts this increase will continue for a further two weeks before an estimated peak around November 15th. This peak is at 186 deaths per day which is low in comparison to the peaks of the first two waves of infection.

Plots of the IFR over time show that from the end of January we estimate a decreasing IFR in all adult age groups, but most steeply in the older ages. This drop indicates the benefits of immunisation against death over and above the benefits against infection. Following this drop, there has been a period of plateau followed by a slight increase to 3.3% (3.1%–3.5%) in the over-75s and 0.27% (0.26%–0.28%) overall. The overall rate represents an increase on the previous week due to a smaller fraction of children becoming infected as a result of the school holiday. Our IFR estimates indicate the children have by far the best survival outcomes from CoVID.

For context, in addition to the data used here, the numbers of reported new positive tests this week (by date of specimen) has declined in comparison to the previous two weeks, though they are highly dependent on the volume and targeting of testing, the public’s testing behaviour and significant reporting delays, and therefore are difficult to interpret. Hospitalisations have started increasing once again, however, while the prevalence of infection, as estimated by the ONS Coronavirus Infection Survey, has instead risen consistently over the last six weeks to 1.9% in England: the highest level it has been in 2021 and close to the highest it has been during the lifetime of the survey.

Summary

Real-time tracking of an epidemic, as data accumulate over time, is an essential component of a public health response to a new outbreak. A team of statistical modellers at the MRC Biostatistics Unit (BSU), University of Cambridge, are working to provide regular now-casts and forecasts of COVID-19 infections and deaths. This information feeds directly to the SAGE sub-group, Scientific Pandemic Influenza sub-group on Modelling (SPI-M), and to regional Public Health England (PHE) teams.

Methods

We fit a transmission model (Birrell et al. 2020) to a number of data sources (see ‘Data Sources’), to reconstruct the number of new COVID-19 infections over time in different age groups and NHS regions, estimate a measure of ongoing transmission and predict the number of new COVID-19 deaths.

Data sources

We use:

  1. Data on COVID-19 confirmed deaths from the Public Health England (PHE) line-listing This consists of a combination of deaths notified to:
    • the Demographics Batch Service (DBS), a mechanism that allows PHE to submit a file of patient information to the National Health Service spine for tracing against the personal demographics service (PDS). PHE submit a line list of patients diagnosed with COVID-19 to DBS daily. The file is returned with a death flag and date of death updated (started 20th March, 2020).
    • NHS England, who report data from NHS trusts relating to patients who have died after admission to hospital or within emergency department settings.
    • Health Protection Teams (HPTs), resulting from a select survey created by PHE to capture deaths occurring outside of hospital settings, e.g. care homes (started 23rd March, 2020)
  2. Data on antibody prevalence in blood samples from a PHE survey of NHS Blood Transfusion (NHSBT) donors.

Data are stratified into eight age groups: <1, 1-4, 5-14, 15-24, 25-44, 45-64, 65-74, 75+, and the NHS England regions (North East and Yorkshire, North West, Midlands, East of England, London, South East, South West).

  1. Published information on the the natural history of COVID-19 (Verity et al., 2020; Li et al, 2020)
  2. Information on contacts between different age groups from:
    • A Survey that describes relative rates of contacts between different age groups (Mossong et al. 2008).
    • Google Community Mobility reports, informing the changes in people’s mobility over the course of the pandemic, particularly after the March 23rd lockdown measures.
    • The ONS’ time use survey, which in conjunction with the google mobility study, allows estimation of the changing exposure to infection risk over time.
    • Data from the Department for Education describing the proportion of children currently attending school.
  3. Daily data on the numbers of people getting immunised by age-group and region. These data are derived from the National Immunisation Management Service (NIMS). These data includes all COVID-19 immunisations administered at hospital hubs, local immunisation service sites such as GP practices, and dedicated immunisation centres.

Epidemic summary

Current \(R_t\)

Value of \(R_t\), the average number of secondary infections due to a typical infection today.

Number of infections

Attack rate

The percentage of a given group that has been infected.

By region

By age

Current IFR

Change in infections incidence

Growth rates

NB: negative growth rates are rates of decline. Values are daily changes.

Region Median 95% CrI (lower) 95% CrI (upper)
England -0.03 -0.03 -0.02
East of England -0.04 -0.06 -0.02
East Midlands -0.04 -0.05 -0.02
London -0.01 -0.03 0.00
North East -0.04 -0.06 -0.01
North West -0.04 -0.06 -0.01
South East -0.01 -0.03 0.00
South West -0.03 -0.04 -0.02
West Midlands -0.04 -0.06 -0.03
Yorkshire and The Humber -0.05 -0.06 -0.03

Halving times

Halving times in days, if a region shows growth than value will be NA.

Region Median 95% CrI (lower) 95% CrI (upper)
England 26.13 21.29 36.15
East of England 19.38 12.07 38.81
East Midlands 17.76 13.05 35.79
London 53.58 21.07 NA
North East 19.28 11.12 54.61
North West 18.20 12.04 46.31
South East 47.17 23.33 310.39
South West 22.76 15.94 41.88
West Midlands 15.22 10.37 26.21
Yorkshire and The Humber 14.51 10.35 27.30

Doubling times

Doubling times in days, if a region shows decline then the value will be NA.

Region Median 95% CrI (lower) 95% CrI (upper)
England NA NA NA
East of England NA NA NA
East Midlands NA NA NA
London NA 243.44 NA
North East NA NA NA
North West NA NA NA
South East NA NA NA
South West NA NA NA
West Midlands NA NA NA
Yorkshire and The Humber NA NA NA

Change in deaths incidence

Growth rates

NB: negative growth rates are rates of decline. Values are daily changes.

Region Median 95% CrI (lower) 95% CrI (upper)
England 0.02 0.01 0.02
East of England 0.01 0.00 0.03
East Midlands 0.01 0.00 0.02
London 0.02 0.01 0.04
North East 0.00 -0.02 0.02
North West 0.00 -0.01 0.02
South East 0.03 0.02 0.05
South West 0.03 0.01 0.04
West Midlands 0.00 -0.01 0.01
Yorkshire and The Humber 0.00 -0.01 0.02

Halving times

Halving times in days, if a region shows growth than value will be NA.

Region Median 95% CrI (lower) 95% CrI (upper)
England NA NA NA
East of England NA 454.44 NA
East Midlands NA 179.70 NA
London NA NA NA
North East NA 45.67 NA
North West NA 62.08 NA
South East NA NA NA
South West NA NA NA
West Midlands NA 54.98 NA
Yorkshire and The Humber 1282.11 52.98 NA

Doubling times

Doubling times in days, if a region shows decline then the value will be NA.

Region Median 95% CrI (lower) 95% CrI (upper)
England 43.29 32.34 61.74
East of England 48.43 23.08 NA
East Midlands 78.42 28.37 NA
London 27.94 17.35 77.46
North East 387.97 32.53 NA
North West 449.45 37.90 NA
South East 20.04 14.28 34.15
South West 26.26 16.99 49.76
West Midlands 7768.57 47.64 NA
Yorkshire and The Humber NA 45.83 NA
## The execution of the prevalence code block will proceed if
##  prev.dat exists and this is TRUE 
##  it is not and external report and this is FALSE

Infections and deaths

The shaded areas show periods of national lockdown, the green lines the dates (once confirmed) of the steps in the roadmap in the UK Governement’s COVID-19 Response – Spring 2021, and the red line shows the date these results were produced (29 Oct).

Infection incidence

By region

By age

Cumulative infections

By region

By age

Deaths incidence

By region

By age

Cumulative deaths

By region

By age

IFR

Prob \(R_t > 1\)

The figure below shows the probability that \(R_t\) is greater than 1 (ie: the number of infections is growing) in each region over time. Clicking the regions in the legend allows lines to be added or removed from the figure.

\(R_t\)

Copyright © MRC Biostatistics Unit, University of Cambridge